Automatic detection of depression symptoms in twitter using multimodal analysis

The Journal of Supercomputing - Depression is the most prevalent mental disorder that can lead to suicide. Due to the tendency of people to share their thoughts on social platforms, social data...     

Fast approximate energy minimization via graph cuts

Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere while preserving sharp discontinuities that may exist, e.g., at object boundaries. These tasks are naturally stated in terms of energy minimization. The authors consider a wide class of energies with various smoothness constraints. Global minimization of these energy functions is NP-hard even in the simplest discontinuity-preserving case. Therefore, our focus is on efficient approximation algorithms. We present two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves, namely expansion moves and swap moves. These moves can simultaneously change the labels of arbitrarily large sets of pixels. In contrast, many standard algorithms (including simulated annealing) use small moves where only one pixel changes its label at a time. Our expansion algorithm finds a labeling within a known factor of the global minimum, while our swap algorithm handles more general energy functions. Both of these algorithms allow important cases of discontinuity preserving energies. We experimentally demonstrate the effectiveness of our approach for image restoration, stereo and motion. On real data with ground truth, we achieve 98 percent accuracy     

Symbiotic artificial immune system

Artificial Immune System algorithms use antibodies that fully specify the solution of an optimization, learning, or pattern recognition problem. By being restricted to fully specified antibodies, an AIS algorithm cannot make use of schemata or classes of partial solutions, while sub solutions can help a lot in faster emergence of a totally good solution in many problems. To exploit schemata in artificial immune systems, this paper presents a novel algorithm that combines traditional artificial immune systems and symbiotic combination operator. The algorithm starts searching with partially specified antibodies and gradually builds more and more specified solutions till it finds complete answers. The algorithm is compared with CLONALG algorithm on several multimodal function optimization and combinatorial optimization problems and it is shown that it is faster than CLONALG on most problems and can find solutions in problems that CLONALG totally fails.     

Report of the Second Workshop on the Usage of NetFlow/IPFIX in Network Management

Following the success of the First Workshop on the Usage of NetFlow/IPFIX (Pras et al. in J Netw Syst Manag 17(4), 2009) in 2008, the European EMANICS Network of Excellence organized a second workshop in October 2009, held at Jacobs University Bremen. This report summarizes the workshop and presents its main conclusions.     

Fuzzy Bayesian system reliability assessment based on Pascal distribution

The main purpose of this paper is to provide a methodology for discussing the fuzzy. Bayesian system reliability from the fuzzy component reliabilities, actually we discuss on the Fuzzy Bayesian system reliability assessment based on Pascal distribution, because the data sometimes cannot be measured and recorded precisely. In order to apply the Bayesian approach, the fuzzy parameters are assumed as fuzzy random variables with fuzzy prior distributions. The (conventional) Bayes estimation method will be used to create the fuzzy Bayes point estimator of system reliability by invoking the well-known theorem called ‘Resolution Identity’ in fuzzy sets theory. On the other hand, we also provide the computational procedures to evaluate the membership degree of any given Bayes point estimate of system reliability. In order to achieve this purpose, we transform the original problem into a nonlinear programming problem. This nonlinear programming problem is then divided into four sub-problems for the purpose of simplifying computation. Finally, the sub problems can be solved by using any commercial optimizers, e.g. GAMS or LINGO.     

The Enhancement of Mine Waste Stability Using Biocementation

Journal of Mining Science - There are large amounts of waste deposits around mines and mineral processing plants, and their instability is one of the major concerns in mining industries. One of the...     

A cost-effective approach to generate accurate correlations via analyzing a minimum number of data points; Case study on the convection heat transfer problem

It is very common in the heat transfer area to analyze and design heat equipment using the past available heat correlations. Basically, demanding higher-accuracy correlations enforces the heat laboratories to test and collect larger banks of laboratory data. However, this conversely affects the laboratory cost. Therefore, it becomes challenging to create new approaches that let the correlation developers use smaller experimental datasets and provide correlations with sufficient accuracies. To surmount this challenge, the present work develops a new approach that benefits from the computational fluid dynamics method as a reliable and cheap tool and adequately enriches the original, insufficient dataset. Then, suitable enhanced correlations are developed using the new enriched experimental-numerical-based dataset. In parallel, the artificial neural network (ANN) is used to enrich the original insufficient dataset separately. Using this experimental-ANN-based dataset, it provides a totally ANN-based correlation. It is shown that the results of enhanced correlations are as accurate as those of the ANN-based correlation. However, the point is that the use of the present approach is about 100 times faster than using the ANN. The typical forced convection heat transfer through a pipe is examined here to show the capabilities of the current approach.     

Synthesis and characterization of ZnO nanoparticles prepared in gelatin media

Zinc oxide nanoparticles (ZnO-NPs) were synthesized via the sol-gel method in gelatin media. Long-chain gelatin compounds were utilized to terminate the growth of ZnO-NPs and to stabilize them. The ZnO-NPs were characterized by a number of techniques, such as X-ray diffraction analysis (XRD), Fourier transform infrared spectroscopy (FTIR), and high-magnification transmission electron microscopy (TEM). The ZnO-NPs calcined at different temperatures exhibited a hexagonal (wurtzite) structure with sizes from 30 to 60 nm. The influence of the calcination temperature on the morphology of ZnO-NPs was also investigated. The results showed that gelatin is an interesting material that can be used as a stabilizer in the sol-gel technique for preparing small ZnO-NPs.     

Characterization of the chemically deposited hydroxyapatite coating on a titanium substrate

Bioactive hydroxyapatite (HA) coating on titanium (Ti) implant can be used as a drug delivery device. A controlled release of drug around the implant requires the incorporation of drug into the coating material during the coating process. HA coating was prepared using a two-step procedure in conditions suitable for simultaneous incorporation of the protein-based drug into the coating material. Monetite coating was deposited on Ti substrate in acidic condition followed by the transformation of the monetite coating to HA. X-ray diffraction (XRD) confirmed the formation of the monetite phase at the first step of the coating preparation, which was transformed into HA at the second step. Fourier transform infrared spectroscopy demonstrated typical bands of a crystallized carbonated HA with A- and B-type substitution, which was confirmed by the XRD refinement of the structural parameters. Scanning electron microscope was used to observe the morphology of monetite and HA coatings. Adhesion of the coatings was measured using a scratch tester. The critical shearing stress was found to be 84.20 ± 1.27 MPa for the monetite coating, and 44.40 ± 2.39 MPa for the HA coating.